DRscDB: A single-cell RNA-seq resource for data mining and data comparison across species

Molecular signature underlying (R)-ketamine rapid antidepressant response on anhedonic-like behavior induced by sustained exposure to stress

Anhedonia induced by sustained stress exposure is a hallmark symptom of major depressive disorder (MDD) and in rodents, it can be accessed through the sucrose preference test (SPT). (R)-ketamine is a fast-acting antidepressant with less detrimental side effects and abuse liability compared to racemic ketamine. The present study combined high-throughput proteomics and network analysis to identify molecular mechanisms involved in chronic variable stress (CVS)-induced anhedonia and promising targets underlying (R)-ketamine rapid antidepressant response. Male Wistar rats were subjected to CVS for five weeks. Based on the SPT, animals were clustered into resilient or anhedonic-like (ANH) groups. ANH rats received a single dose of saline or (R)-ketamine (20 mg/kg, i.p.), which was proceeded by treatment response evaluation. After prefrontal cortex collection, proteomic analysis was performed to uncover the differentially expressed proteins (DEPs) related to both anhedonic-like behavior and pharmacological response. The behavioral assessment showed that the ANH animals had a significant decrease in SPT, and that (R)-ketamine responders showed a reversal of anhedonic-like behavior. On a molecular level, anhedonia-like behavior was associated with the downregulation of Neuronal Pentraxin Receptor (Nptxr) and Galectin-1 (Gal-1). These data reinforce a disruption in the inflammatory response, neurotransmitter receptor activity, and glutamatergic synapses in chronic stress-induced anhedonia. (R)-ketamine response-associated DEPs included novel potential targets involved in the modulation of oxidative stress, energetic metabolism, synaptogenesis, dendritic arborization, neuroinflammation, gene expression, and telomere length, converging to biological themes extensively documented in MDD physiopathology. Our data provide valuable insights into the molecular mechanisms underlying the response to (R)-ketamine and highlight these pathways as potential therapeutic targets for anhedonia. By addressing proteins involved in oxidative stress, energy metabolism, synaptogenesis, dendritic arborization, neuroinflammation, gene expression, and telomere length, we can target multiple key factors involved in the pathophysiology of MDD. Modulating these proteins could open avenues for novel therapeutic strategies and deepen our understanding of anhedonia, offering hope for improved outcomes in individuals facing this challenging condition. However, additional studies will be essential to validate these findings and further explore their therapeutic implications.

FlyRNAi.org 2025 update-expanded resources for new technologies and species

The design, analysis and mining of large-scale 'omics studies with the goal of advancing biological and biomedical understanding require use of a range of bioinformatics tools, including approaches tailored to needs specific to a given species and/or technology. The FlyRNAi database at the Drosophila RNAi Screening Center and Transgenic RNAi Project (DRSC/TRiP) Functional Genomics Resources (https://fgr.hms.harvard.edu/tools) supports an increasingly broad group of technologies and species. Recently, for example, we expanded the database to include additional new data-centric resources that facilitate mining and analysis of single-cell transcriptomics. In addition, we have applied our approaches to CRISPR reagent and gene-centric bioinformatics approaches in Drosophila to arthropod vectors of infectious diseases. Building on our previous comprehensive reports on the FlyRNAi database, here we focus on new and updated resources with a primary focus on data-centric tools. Altogether, our suite of online resources supports various stages of functional genomics studies for Drosophila and other arthropods, and facilitate a wide range of reagent design, analysis, data mining and analysis approaches by biologists and biomedical experts studying Drosophila, other common genetic model species, arthropod vectors and/or human biology.

Aging is associated with a modality-specific decline in taste

Deficits in chemosensory processing are associated with healthy aging, as well as numerous neurodegenerative disorders, including Alzheimer's disease (AD). The fruit fly, Drosophila melanogaster, is a powerful model for studying chemosensation, aging, and aging-related pathologies, yet the effects of aging and neurodegeneration on taste function remain largely unexplored. Aging impaired response to sugars, but not medium-chain fatty acids that are sensed by a shared population of neurons. Selective expression of the human amyloid beta (Aβ) peptide phenocopied the effects of aging. Functional imaging of gustatory axon terminals revealed reduced response to sugar, but not fatty acids. Axonal innervation of the fly taste center was largely intact in aged flies; however, axonal innervation was reduced upon expression of Aβ. A comparison of transcript expression within the sugar-sensing taste neurons revealed age-related changes in 66 genes. Together, these findings suggest that different mechanisms underly taste deficits in aged and AD model flies.

Quest for Orthologs in the Era of Biodiversity Genomics

The era of biodiversity genomics is characterized by large-scale genome sequencing efforts that aim to represent each living taxon with an assembled genome. Generating knowledge from this wealth of data has not kept up with this pace. We here discuss major challenges to integrating these novel genomes into a comprehensive functional and evolutionary network spanning the tree of life. In summary, the expanding datasets create a need for scalable gene annotation methods. To trace gene function across species, new methods must seek to increase the resolution of ortholog analyses, e.g. by extending analyses to the protein domain level and by accounting for alternative splicing. Additionally, the scope of orthology prediction should be pushed beyond well-investigated proteomes. This demands the development of specialized methods for the identification of orthologs to short proteins and noncoding RNAs and for the functional characterization of novel gene families. Furthermore, protein structures predicted by machine learning are now readily available, but this new information is yet to be integrated with orthology-based analyses. Finally, an increasing focus should be placed on making orthology assignments adhere to the findable, accessible, interoperable, and reusable (FAIR) principles. This fosters green bioinformatics by avoiding redundant computations and helps integrating diverse scientific communities sharing the need for comparative genetics and genomics information. It should also help with communicating orthology-related concepts in a format that is accessible to the public, to counteract existing misinformation about evolution.

Identifying an immunosenescence-associated gene signature in gastric cancer by integrating bulk and single-cell sequencing data

It has been believed that immunosenescence plays a crucial role in tumorigenesis and cancer therapy. Nevertheless, there is still a lack of understanding regarding its role in determining clinical outcomes and therapy selection for gastric cancer patients, due to the lack of a feasible immunosenescence signature. Therefore, this research aims to develop a gene signature based on immunosenescence, which is used for stratification of gastric cancer. By integrative analysis of bulk transcriptome and single-cell data, we uncovered immunosenescence features in gastric cancer. Random forest algorithm was used to select hub genes and multivariate Cox algorithm was applied to construct a scoring system to evaluate the prognosis and the response to immunotherapy and chemotherapy. The Cancer Genome Atlas of Stomach Adenocarcinoma (TCGA-STAD) cohort was implemented as the training cohort and two independent cohorts from the Gene Expression Omnibus (GEO) database were used for validation. The model was further tested by our Fudan cohort. In this study, immunosenescence was identified as a hallmark of gastric cancer that is linked with transcriptomic features, genomic variations, and distinctive tumor microenvironment (TME). Four immunosenescence genes, including APOD, ADIPOR2, BRAF, and C3, were screened out to construct a gene signature for risk stratification. Higher risk scores indicated strong predictive power for poorer overall survival. Notably, the risk score signature could reliably predict response to chemotherapy and immunotherapy, with patients with high scores benefiting from immunotherapy and patients with low scores responding to chemotherapy. We report immunosenescence as a hitherto unheralded hallmark of gastric cancer that affects prognosis and treatment efficiency.

Asporin and CD109, expressed in the injured neonatal spinal cord, attenuate axonal re-growth in vitro

Axonal regeneration is restricted in adults and causes irreversible motor dysfunction following spinal cord injury (SCI). In contrast, neonates have prominent regenerative potential and can restore their neural function. Although the distinct cellular responses in neonates have been studied, how they contribute to neural recovery remains unclear. To assess whether the secreted molecules in neonatal SCI can enhance neural regeneration, we re-analyzed the previously performed single-nucleus RNA-seq (snRNA-seq) and focused on Asporin and Cd109, the highly expressed genes in the injured neonatal spinal cord. In the present study, we showed that both these molecules were expressed in the injured spinal cords of adults and neonates. We treated the cortical neurons with recombinant Asporin or CD109 to observe their direct effects on neurons in vitro. We demonstrated that these molecules enhance neurite outgrowth in neurons. However, these molecules did not enhance re-growth of severed axons. Our results suggest that Asporin and CD109 influence neurites at the lesion site, rather than promoting axon regeneration, to restore neural function in neonates after SCI.

From whole bodies to single cells: A guide to transcriptomic approaches for ecology and evolutionary biology

RNA sequencing (RNAseq) methodology has experienced a burst of technological developments in the last decade, which has opened up opportunities for studying the mechanisms of adaptation to environmental factors at both the organismal and cellular level. Selecting the most suitable experimental approach for specific research questions and model systems can, however, be a challenge and researchers in ecology and evolution are commonly faced with the choice of whether to study gene expression variation in whole bodies, specific tissues, and/or single cells. A wide range of sometimes polarised opinions exists over which approach is best. Here, we highlight the advantages and disadvantages of each of these approaches to provide a guide to help researchers make informed decisions and maximise the power of their study. Using illustrative examples of various ecological and evolutionary research questions, we guide the readers through the different RNAseq approaches and help them identify the most suitable design for their own projects.

Transcriptional programs mediating neuronal toxicity and altered glial-neuronal signaling in a Drosophila knock-in tauopathy model

Missense mutations in the gene encoding the microtubule-associated protein TAU (current and approved symbol is MAPT) cause autosomal dominant forms of frontotemporal dementia. Multiple models of frontotemporal dementia based on transgenic expression of human TAU in experimental model organisms, including Drosophila, have been described. These models replicate key features of the human disease but do not faithfully recreate the genetic context of the human disorder. Here we use CRISPR-Cas-mediated gene editing to model frontotemporal dementia caused by the TAU P301L mutation by creating the orthologous mutation, P251L, in the endogenous Drosophila tau gene. Flies heterozygous or homozygous for Tau P251L display age-dependent neurodegeneration, display metabolic defects, and accumulate DNA damage in affected neurons. To understand the molecular events promoting neuronal dysfunction and death in knock-in flies, we performed single-cell RNA sequencing on approximately 130,000 cells from brains of Tau P251L mutant and control flies. We found that expression of disease-associated mutant tau altered gene expression cell autonomously in all neuronal cell types identified. Gene expression was also altered in glial cells, suggestive of non-cell-autonomous regulation. Cell signaling pathways, including glial-neuronal signaling, were broadly dysregulated as were brain region and cell type-specific protein interaction networks and gene regulatory programs. In summary, we present here a genetic model of tauopathy that faithfully recapitulates the genetic context and phenotypic features of the human disease, and use the results of comprehensive single-cell sequencing analysis to outline pathways of neurotoxicity and highlight the potential role of non-cell-autonomous changes in glia.

Neuronal excitability modulates developmental time of Drosophila melanogaster

Developmental time is a fundamental life history trait that affects the reproductive success of animals. Developmental time is known to be regulated by many genes and environmental conditions, yet mechanistic understandings of how various cellular processes influence the developmental timing of an organism are lacking. The nervous system is known to control key processes that affect developmental time, including the release of hormones that signal transitions between developmental stages. Here we show that the excitability of neurons plays a crucial role in modulating developmental time. Genetic manipulation of neuronal excitability in Drosophila melanogaster alters developmental time, which is faster in animals with increased neuronal excitability. We find that selectively modulating the excitability of peptidergic neurons is sufficient to alter developmental time, suggesting the intriguing hypothesis that the impact of neuronal excitability on DT may be at least partially mediated by peptidergic regulation of hormone release. This effect of neuronal excitability on developmental time is seen during embryogenesis and later developmental stages. Observed phenotypic plasticity in the effect of genetically increasing neuronal excitability at different temperatures, a condition also known to modulate excitability, suggests there is an optimal level of neuronal excitability, in terms of shortening DT. Together, our data highlight a novel connection between neuronal excitability and developmental time, with broad implications related to organismal physiology and evolution.

Aging is associated with a modality-specific decline in taste

Deficits in chemosensory processing are associated with healthy aging, as well as numerous neurodegenerative disorders, including Alzheimer's Disease (AD). In many cases, chemosensory deficits are harbingers of neurodegenerative disease, and understanding the mechanistic basis for these changes may provide insight into the fundamental dysfunction associated with aging and neurodegeneration. The fruit fly, Drosophila melanogaster , is a powerful model for studying chemosensation, aging, and aging-related pathologies, yet the effects of aging and neurodegeneration on chemosensation remain largely unexplored in this model, particularly with respect to taste. To determine whether the effects of aging on taste are conserved in flies, we compared the response of flies to different appetitive tastants. Aging impaired response to sugars, but not medium-chain fatty acids that are sensed by a shared population of neurons, revealing modality-specific deficits in taste. Selective expression of the human amyloid beta (Aβ) 1-42 peptide bearing the Arctic mutation (E693E) associated with early onset AD in the neurons that sense sugars and fatty acids phenocopies the effects of aging, suggesting that the age-related decline in response is localized to gustatory neurons. Functional imaging of gustatory axon terminals revealed reduced response to sugar, but not fatty acids. Axonal innervation of the fly taste center was largely intact in aged flies, suggesting that reduced sucrose response does not derive from neurodegeneration. Conversely, expression of the amyloid peptide in sweet-sensing taste neurons resulted in reduced innervation of the primary fly taste center. A comparison of transcript expression within the sugar-sensing taste neurons revealed age-related changes in 66 genes, including a reduction in odorant-binding protein class genes that are also expressed in taste sensilla. Together, these findings suggest that deficits in taste detection may result from signaling pathway-specific changes, while different mechanisms underly taste deficits in aged and AD model flies. Overall, this work provides a model to examine cellular deficits in neural function associated with aging and AD.

Glucocerebrosidase deficiency leads to neuropathology via cellular immune activation

Mutations in GBA (glucosylceramidase beta), which encodes the lysosomal enzyme glucocerebrosidase (GCase), are the strongest genetic risk factor for the neurodegenerative disorders Parkinson's disease (PD) and Lewy body dementia. Recent work has suggested that neuroinflammation may be an important factor in the risk conferred by GBA mutations. We therefore systematically tested the contributions of immune-related genes to neuropathology in a Drosophila model of GCase deficiency. We identified target immune factors via RNA-Seq and proteomics on heads from GCase-deficient flies, which revealed both increased abundance of humoral factors and increased macrophage activation. We then manipulated the identified immune factors and measured their effect on head protein aggregates, a hallmark of neurodegenerative disease. Genetic ablation of humoral (secreted) immune factors did not suppress the development of protein aggregation. By contrast, re-expressing Gba1b in activated macrophages suppressed head protein aggregation in Gba1b mutants and rescued their lifespan and behavioral deficits. Moreover, reducing the GCase substrate glucosylceramide in activated macrophages also ameliorated Gba1b mutant phenotypes. Taken together, our findings show that glucosylceramide accumulation due to GCase deficiency leads to macrophage activation, which in turn promotes the development of neuropathology.

Molecular traces of Drosophila hemocytes reveal transcriptomic conservation with vertebrate myeloid cells

Drosophila hemocytes serve as the primary defense system against harmful threats, allowing the animals to thrive. Hemocytes are often compared to vertebrate innate immune system cells due to the observed functional similarities between the two. However, the similarities have primarily been established based on a limited number of genes and their functional homologies. Thus, a systematic analysis using transcriptomic data could offer novel insights into Drosophila hemocyte function and provide new perspectives on the evolution of the immune system. Here, we performed cross-species comparative analyses using single-cell RNA sequencing data from Drosophila and vertebrate immune cells. We found several conserved markers for the cluster of differentiation (CD) genes in Drosophila hemocytes and validated the role of CG8501 (CD59) in phagocytosis by plasmatocytes, which function much like macrophages in vertebrates. By comparing whole transcriptome profiles in both supervised and unsupervised analyses, we showed that Drosophila hemocytes are largely homologous to vertebrate myeloid cells, especially plasmatocytes to monocytes/macrophages and prohemocyte 1 (PH1) to hematopoietic stem cells. Furthermore, a small subset of prohemocytes with hematopoietic potential displayed homology with hematopoietic progenitor populations in vertebrates. Overall, our results provide a deeper understanding of molecular conservation in the Drosophila immune system.

REPTOR and CREBRF encode key regulators of muscle energy metabolism

Metabolic flexibility of muscle tissue describes the adaptive capacity to use different energy substrates according to their availability. The disruption of this ability associates with metabolic disease. Here, using a Drosophila model of systemic metabolic dysfunction triggered by yorkie-induced gut tumors, we show that the transcription factor REPTOR is an important regulator of energy metabolism in muscles. We present evidence that REPTOR is activated in muscles of adult flies with gut yorkie-tumors, where it modulates glucose metabolism. Further, in vivo studies indicate that sustained activity of REPTOR is sufficient in wildtype muscles to repress glycolysis and increase tricarboxylic acid (TCA) cycle metabolites. Consistent with the fly studies, higher levels of CREBRF, the mammalian ortholog of REPTOR, reduce glycolysis in mouse myotubes while promoting oxidative metabolism. Altogether, our results define a conserved function for REPTOR and CREBRF as key regulators of muscle energy metabolism.

Integrative multi-omics and systems bioinformatics in translational neuroscience: A data mining perspective

Bioinformatic analysis of large and complex omics datasets has become increasingly useful in modern day biology by providing a great depth of information, with its application to neuroscience termed neuroinformatics. Data mining of omics datasets has enabled the generation of new hypotheses based on differentially regulated biological molecules associated with disease mechanisms, which can be tested experimentally for improved diagnostic and therapeutic targeting of neurodegenerative diseases. Importantly, integrating multi-omics data using a systems bioinformatics approach will advance the understanding of the layered and interactive network of biological regulation that exchanges systemic knowledge to facilitate the development of a comprehensive human brain profile. In this review, we first summarize data mining studies utilizing datasets from the individual type of omics analysis, including epigenetics/epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, and spatial omics, pertaining to Alzheimer's disease, Parkinson's disease, and multiple sclerosis. We then discuss multi-omics integration approaches, including independent biological integration and unsupervised integration methods, for more intuitive and informative interpretation of the biological data obtained across different omics layers. We further assess studies that integrate multi-omics in data mining which provide convoluted biological insights and offer proof-of-concept proposition towards systems bioinformatics in the reconstruction of brain networks. Finally, we recommend a combination of high dimensional bioinformatics analysis with experimental validation to achieve translational neuroscience applications including biomarker discovery, therapeutic development, and elucidation of disease mechanisms. We conclude by providing future perspectives and opportunities in applying integrative multi-omics and systems bioinformatics to achieve precision phenotyping of neurodegenerative diseases and towards personalized medicine.

A pleiotropic chemoreceptor facilitates the production and perception of mating pheromones

Optimal mating decisions depend on the robust coupling of signal production and perception because independent changes in either could carry a fitness cost. However, since the perception and production of mating signals are often mediated by different tissues and cell types, the mechanisms that drive and maintain their coupling remain unknown for most animal species. Here, we show that in Drosophila, behavioral responses to, and the production of, a putative inhibitory mating pheromone are co-regulated by Gr8a, a member of the Gustatory receptor gene family. Specifically, through behavioral and pheromonal data, we found that Gr8a independently regulates the behavioral responses of males and females to a putative inhibitory pheromone, as well as its production in the fat body and oenocytes of males. Overall, these findings provide a relatively simple molecular explanation for how pleiotropic receptors maintain robust mating signaling systems at the population and species levels.

Single-cell transcriptomics to understand the cellular heterogeneity in toxicology

Background

Identification of molecular signatures from omics studies is widely applied in toxicological studies, and the evaluation of potential toxic effects provides novel insights into molecular resolution.

Objective

The prediction of toxic effects and drug tolerance provides important clues regarding the mode of action of target compounds. However, heterogeneity within samples makes toxicology studies challenging because the purity of the target cell in the samples remains unknown until their actual utilization.

Result

Single-cell resolution studies have been suggested in toxicogenomics, and several studies have explained toxic effects and drug tolerance using heterogeneous cells in both in vivo and in vitro conditions. In this review, we presented an understanding of single-cell transcriptomes and their applications in toxicogenomics.

Conclusion

The most toxicological mechanism in organisms occurs through intramolecular combinations, and heterogeneity issues have reached a surmountable level. We hope this review provides insights to successfully conduct future studies on toxicology.

Purpose of the review

Toxicogenomics is an interdisciplinary field between toxicology and genomics that was successfully applied to construct molecular profiles in a broad spectrum of toxicology. However, heterogeneity within samples makes toxicology studies challenging because the purity of target cell in the samples remains unknown until their actual utilisation. In this review, we presented an understanding of single-cell transcriptomes and their applications in toxicogenomics.

Recent findings

A high-throughput techniques have been used to understand cellular heterogeneity and molecular mechanisms at toxicogenomics. Single-cell resolution analysis is required to identify biomarkers of explain toxic effect and in order to understand drug tolerance.

Multifaceted roles of SARM1 in axon degeneration and signaling

Axons are considered to be particularly vulnerable components of the nervous system; impairments to a neuron’s axon leads to an effective silencing of a neuron’s ability to communicate with other cells. Nervous systems have therefore evolved plasticity mechanisms for adapting to axonal damage. These include acute mechanisms that promote the degeneration and clearance of damaged axons and, in some cases, the initiation of new axonal growth and synapse formation to rebuild lost connections. Here we review how these diverse processes are influenced by the therapeutically targetable enzyme SARM1. SARM1 catalyzes the breakdown of NAD+, which, when unmitigated, can lead to rundown of this essential metabolite and axonal degeneration. SARM1’s enzymatic activity also triggers the activation of downstream signaling pathways, which manifest numerous functions for SARM1 in development, innate immunity and responses to injury. Here we will consider the multiple intersections between SARM1 and the injury signaling pathways that coordinate cellular adaptations to nervous system damage.

Analysis of Single-Cell Transcriptome Data in Drosophila

The fly Drosophila is a versatile model organism that has led to fascinating biological discoveries. In the past few years, Drosophila researchers have used single-cell RNA-sequencing (scRNA-seq) to gain insights into the cellular composition, and developmental processes of various tissues and organs. Given the success of single-cell technologies a variety of computational tools and software packages were developed to enable and facilitate the analysis of scRNA-seq data. In this book chapter we want to give guidance on analyzing droplet-based scRNA-seq data from Drosophila. We will initially describe the preprocessing commonly done for Drosophila, point out possible downstream analyses, and finally highlight computational methods developed using Drosophila scRNA-seq data.

Single-cell analysis of mosquito hemocytes identifies signatures of immune cell subtypes and cell differentiation

Mosquito immune cells, known as hemocytes, are integral to cellular and humoral responses that limit pathogen survival and mediate immune priming. However, without reliable cell markers and genetic tools, studies of mosquito immune cells have been limited to morphological observations, leaving several aspects of their biology uncharacterized. Here, we use single-cell RNA sequencing (scRNA-seq) to characterize mosquito immune cells, demonstrating an increased complexity to previously defined prohemocyte, oenocytoid, and granulocyte subtypes. Through functional assays relying on phagocytosis, phagocyte depletion, and RNA-FISH experiments, we define markers to accurately distinguish immune cell subtypes and provide evidence for immune cell maturation and differentiation. In addition, gene-silencing experiments demonstrate the importance of lozenge in defining the mosquito oenocytoid cell fate. Together, our scRNA-seq analysis provides an important foundation for future studies of mosquito immune cell biology and a valuable resource for comparative invertebrate immunology.